Efficient Models
We select and optimize models for low-watt, low-latency inference—quantization, caching, and adaptive batching included.
We’re building a decentralized AI network that runs on everyday devices instead of massive, water-hungry data centers—cutting energy by up to 70% and water by up to 90% while keeping responses fast and accurate.
AI is the future—but it shouldn’t drain the planet to get there. Eco-AI routes inference across a global mesh of consumer-owned nodes, prioritizing renewable power and efficiency without sacrificing quality.
Under the hood: efficient models, smart routing, and a decentralized fleet.
We select and optimize models for low-watt, low-latency inference—quantization, caching, and adaptive batching included.
Requests prefer nodes powered by solar, wind, or nuclear when available, balancing performance and sustainability.
Node operators earn for queries they serve. As devices upgrade, the network automatically gets faster.
We design for minimal footprint—then optimize again.
Transparent docs, APIs, and a community-driven roadmap.
Privacy-respecting, secure by design, clear pricing.
We ship, measure, iterate—fast.
Value flows to the people who power the network.
Great AI for everyone—not just those with the biggest servers.
We’re a small, senior group across ML, distributed systems, and climate tech. We bias toward shipping and measurable impact.
From a question—“Can AI scale without scaling emissions?”—to a growing global network.
Built the first decentralized inference prototype on consumer GPUs.
Launched Eco-AI chat and opened node onboarding. Early adopters powered millions of queries sustainably.
Compliance, private routing, and research partnerships around energy-aware scheduling.
Try Eco-AI, or run a node and earn by powering green AI.